How do you analyze marketing and growth data in Metabase?
Marketing and growth tools hold the record of how you acquire and keep customers: ad spend, traffic, search visibility, product activation, and lifecycle email. In Metabase, bring daily aggregates of those signals into a SQL database and model adjacent layers for ad performance, traffic rollups, product events, and email engagement. Those layers support dashboards for ROAS, CAC, funnel conversion, organic search, retention, and deliverability — next to the revenue data the rest of the company already reports on.
TL;DR — Never sync raw click or event streams into a BI warehouse. Sync daily stats by campaign and channel, traffic rollups, event rollups, and engagement counts. MCP is useful for live exploration; durable marketing reporting needs database-backed syncs and history.
Which tools does this cover?
- Google Ads — campaign daily stats, campaigns, ad groups, ads
- Meta Ads — ad set daily insights, campaigns, ad sets, ads
- LinkedIn Ads — campaign daily analytics, campaign groups, campaigns, creatives
- TikTok Ads — ad group daily stats, campaigns, ad groups, ads
- Google Analytics 4 — session and event rollups, events, sessions, users
- Google Tag Manager — container configuration snapshots, containers, tags, triggers
- Google Search Console — search performance rows, queries, pages, countries and devices
- Google AdSense — earnings reports, sites, ad units, country splits
- Plausible Analytics — visitor and pageview aggregates, sources and UTM campaigns, goals and conversions, entry pages
- Amplitude — event rollups, events, users, cohorts
- PostHog — event rollups, events, persons, sessions
- Mixpanel — event rollups, events, user profiles, identity mappings
- AppsFlyer — attributed installs, in-app events, retargeting conversions, SKAN reports
- Mailchimp — campaign reports, campaigns, audiences (lists), subscribers
- ActiveCampaign — campaign engagement records, contacts, lists, automations
- SendGrid — daily delivery stats, message events (webhook), suppressions, marketing contacts
- Postmark — outbound message records, opens and clicks, bounces, daily outbound stats
- Resend — email events (webhooks), emails, broadcasts, audiences and contacts
For the revenue side of the same story, cross-link the shared model to HubSpot, Stripe, and Shopify — spend and revenue together power CAC and ROAS you can trust.
What is the shared marketing data model?
| Concept | Common terms | Used for |
|---|---|---|
| Ad performance | Campaign, ad set/group, daily stats, spend | ROAS, CPC, CTR, budget pacing |
| Traffic rollup | Sessions, channel, source/medium, landing page | Conversion rate, acquisition mix |
| Search performance | Query, page, clicks, impressions, position | Organic visibility and CTR |
| Product event rollup | Event, user, cohort, activation | Activation and retention |
| Campaign engagement | Sends, delivered, clicks, bounces, unsubscribes | Email CTR and deliverability |
| Lead / signup | Lead, contact, form fill, registration | Cost per lead, funnel conversion |
| Customer | Won deal, subscription, first purchase | CAC and LTV joins |
| Channel | UTM source/medium/campaign, media source | The join key for everything above |
How do you connect marketing tools to Metabase?
- MCP + CLI route — pull a scoped, summarized export through an MCP server, save CSV, and load it with
mb upload csvfor fast exploration. - Pipeline route — sync daily stats, rollups, and entities into a database or warehouse with a connector or API pipeline, then build reliable dashboards.
- Cross-source route — join spend, traffic, product, and email data to CRM and revenue to explain outcomes, not just activity.
What can you analyze across these tools?
- ROAS — conversion value over ad spend, by campaign and channel
- Customer acquisition cost — spend over new customers, blended or paid-only
- Cost per lead — spend over leads, raw and qualified
- Cost per click — the price of attention, per channel
- Click-through rate — clicks over impressions or delivered emails
- Landing-page conversion rate — conversions over sessions, per page
- Organic clicks & impressions — search visibility and what it earns
- Activation rate — signups reaching the product's value moment
- Conversion rate andLTV — the funnel and value pair that closes the loop
Which dashboards should you build?
- Paid channel performance — spend, ROAS, and efficiency across ad platforms
- Ad spend pacing — budget burn against plan, with projections
- Marketing funnel — visit to signup to customer, by channel and campaign
- Organic search performance — queries, pages, and branded vs. non-branded clicks
- Paid vs. organic mix — the acquisition balance over time
- Product retention — activation, cohorts, and channel quality
- Email engagement — campaign performance, deliverability, and list health
Common mistakes
Syncing raw click or event streams into the warehouse.→ Daily aggregates by campaign, channel, and page answer the reporting questions. Raw streams belong in the source tools — or in GA4's BigQuery export if you genuinely need events.
Summing platform-reported conversions across platforms.→ Each platform attributes under its own model and window — the same purchase can appear in three of them. Keep per-platform columns or count conversions from your own database.
Reporting sitewide conversion rate as one number.→ Channel mix drives it more than site quality. Segment by channel and landing page, and watch the segments.
Treating email opens as engagement.→ Apple Mail Privacy Protection inflates opens. Anchor on click-through rate and downstream conversions.
Letting UTM taxonomy drift.→ UTM source, medium, and campaign are the join keys for the whole model. Publish a naming convention and validate it in the pipeline.
Related
Analytics
Integrations
FAQ
What is marketing and growth analytics?
Marketing and growth analytics is reporting built on the record of how you acquire and keep customers — ad spend, traffic, funnels, product activation, and lifecycle email — synced into a SQL database and analyzed in Metabase. Instead of tab-hopping between platform UIs, it answers cross-channel questions: what does a customer cost, which channels send users who stay, and where does the funnel leak? See the marketing analytics overview for the full build, and ROAS and CAC for the core metrics.
Does Metabase connect natively to Google Ads or GA4?
No — Metabase reads SQL databases and warehouses, not SaaS APIs. Sync each tool's daily stats into a database first with a connector or API pipeline, then point Metabase at that database. GA4 is the friendly exception: its native BigQuery export lands raw events in a warehouse Metabase queries directly. For a quick first pass on any tool, pull a summarized export and load it with the Metabase CLI (
mb upload csv). Each guide — Google Ads, GA4, Amplitude — documents both routes.Should Metabase replace my ad platform dashboards?
No — pair them. Platform dashboards in Google Ads or Meta Ads are built for campaign operations, and they should keep that job. Metabase adds what they can't do: one governed view across every channel, joins with CRM and revenue data, and metric definitions that don't change when a platform redesigns its UI. The marketing analytics overview covers how the layers divide the work.
How do I compare performance across ad platforms?
Union each platform's daily stats into one
ad_performance_daily model with consistent channel, campaign, date, spend, and conversion columns — the paid channel performance dashboard is built on exactly that. One honest caveat belongs on the dashboard: each platform self-reports conversions under its own attribution model, so cross-channel ROAS is directional. For a single source of truth, count conversions from your own database or CRM.Can I connect marketing spend to product outcomes?
Yes — that join is the reason to warehouse this data. Users from Amplitude, PostHog, or Mixpanel carry an acquisition channel; ad platforms report spend by channel. Together they power CAC by channel, activation rate by channel, and retention by channel — the "which channels send users who stay" view on the product retention dashboard that no single tool provides.
Which tools does the marketing and growth category cover?
Eighteen tools across four groups: paid media (Google Ads, Meta Ads, LinkedIn Ads, TikTok Ads), web analytics (GA4, Google Tag Manager, Search Console, AdSense, Plausible), product analytics and attribution (Amplitude, PostHog, Mixpanel, AppsFlyer), and email (Mailchimp, ActiveCampaign, SendGrid, Postmark, Resend). All map onto the same shared model, so the dashboards work regardless of which tools you run.
Which dashboards should you build first from marketing data?
Start with paid channel performance if you buy ads — it needs only daily stats from your ad platforms. Add the marketing funnel once traffic and signup data land, then organic search performance from Search Console and email engagement as those sources sync. Product retention rounds out the set when product analytics arrives.